Alzheimer?s disease (AD) affects half the US population over the age of 85 and is characterized by cognitive impairment and reduced life expectancy. Despite extensive clinical and genomic studies, the mechanisms of development and progression of AD remain elusive. Microglia and other myeloid origin cells (collectively called human brain immune cells, or HBICs) have recently emerged as crucial players in the pathogenesis of AD. This is supported through genetic association studies, where many of the common and rare risk loci affect genes that are preferentially or selectively expressed in HBICs, emphasizing the pivotal role of the innate immune system in AD. In addition, single cell RNA sequencing analysis in mouse models of AD has identified a microglia subpopulation that is present at sites of neurodegeneration. It is unclear if HBICs assume a protective or damaging role, but that might vary depending on the stage and progression of AD. Therefore, further analysis of microglia and other immune cells purified from human brains is needed to understand the state of HBIC activity in human AD at different stages of disease. As HBICs constitute a small proportion of total brain cells, homogenate-based studies in human brain tissue are unlikely to capture the full spectrum of HBIC molecular signatures, especially in light of the growing appreciation for the diversity of HBICs in the brain. The proposed work addresses some of the limitations of previous research and is focused on: (1) cell type specific and single cell studies in immune cells isolated from human brain tissue; and (2) a systematic study of the regulatory effects of non-coding DNA on gene and protein expression, which is necessary given that the majority of common risk variants are situated in non-coding regions of the genome. More specifically, our application is uniquely designed to: (1) apply innovative genomic approaches and generate multi-omics data from HBICs isolated from 300 donors, including whole genome sequencing, RNAseq, ATACseq, HiC chromosome conformation capture and proteomics; (2) perform state-of-the-art single cell analysis that will allow us to assess the diversity of HBIC subpopulations, as well as detect those that are associated with AD; (3) connect AD risk loci with changes in the regulatory mechanisms of gene and protein expression in HBICs; and (4) organize HBIC multiscale data in functional networks and identify key drivers for AD. Our overall hypothesis is that HBIC subpopulations assume a neuroprotective role during aging and early stages of AD, but as disease progresses, specific HBIC subpopulations transform to neuroinflammatory phenotype(s). This conversion is partially driven by AD risk genetic variants, which affect regulatory mechanisms of genes that are key drivers of neuroinflammatory HBIC subpopulations. Successful completion of the proposed studies will provide: (1) an increased mechanistic understanding of dysfunction in AD risk loci; (2) prioritization of significant loci and genes for future mechanistic studies; and (3) access to large-scale, multidimensional datasets, together with systems level analyses of these datasets for transcriptional regulation in HBICs, which is an urgently needed (and currently missing) resource.